This publication constitutes half III of the refereed four-volume post-conference court cases of the 4th IFIP TC 12 overseas convention on machine and Computing applied sciences in Agriculture, CCTA 2010, held in Nanchang, China, in October 2010. The 352 revised papers provided have been rigorously chosen from quite a few submissions. They disguise quite a lot of fascinating theories and purposes of data expertise in agriculture, together with simulation types and decision-support platforms for agricultural creation, agricultural product caliber trying out, traceability and e-commerce expertise, the applying of data and verbal exchange expertise in agriculture, and common info carrier know-how and repair platforms improvement in rural areas.

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Each functionality rule is supported by way of particular examples, and code snippets can be found at the book's better half website. the foundations comprise how to:

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Keywords: Mobile devices, data transmission, security, XML encryption, SSL protocol. 1 Introduction Due to the flexible and customizable feature, wireless mobile devices agree with the special requirements of the agriculture application, such as wide region and poor infrastructure condition. Therefore, related application based on wireless mobile devices will become the development direction of agricultural information system. However, the smallness and portable characteristics also cause the security problems of the sensitive data seem more outstanding.

Image Segmentation (a)(b)(c) Figure trisection Pixel number and area ratio as shown in Table 1: Table 1. The number of pixels per plant and the area ratio of crop S1crop S 2 crop S3 crop Sthe total pixel area the number of pixels 2417 area ratio 2417/144000 2066 1062 144000 2066/144000 1062/144000 144000/144000 Target Recognition for the Automatically Targeting Variable Rate Sprayer 27 Drawn from Table 1 that each plant crops the number of pixels in the image and its corresponding area ratio. 6 Conclusion 1) Adopt green strength of RGB`s method to identify the crop from the background of elaphic, the recognition accuracy was more than 98%.